Aspects of the statistical analysis of climate experiments with multiple integrations

Many modern climate experiments consist of multiple General Circulation Model (GCM) integrations. Many experiments also contain climate integrations in which a climate equilibrium is not obtained for a considerable period of time, or in which the mean state slowly evolves with time in response to slowly changing external conditions (such as the concentration of CO2 In this paper we describe some relatively simple statistical techniques which test for the presence of trend and take its effects into account when studying simulated inter-annual variability. The limitations of these methods, the assumptions which are implicit in their use, and techniques for developing tests of hypothesis are all discussed

How does dynamical downscaling affect model biases and future projections of explosive extratropical cyclones along North America’s Atlantic coast?

Explosive extratropical cyclones (EETCs) are rapidly intensifying low pressure systems that generate severe weather along North America’s Atlantic coast. Global climate models (GCMs) tend to simulate too few EETCs, perhaps partly due to their coarse horizontal resolution and poorly resolved moist diabatic processes. This study explores whether dynamical downscaling can reduce EETC frequency biases, and whether this affects future projections of storms along North America’s Atlantic coast. A regional climate model (CanRCM4) is forced with the CanESM2 GCM for the periods 1981 to 2000 and 2081 to 2100. EETCs are tracked from relative vorticity using an objective feature tracking algorithm. CanESM2 simulates 38% fewer EETC tracks compared to reanalysis data, which is consistent with a negative Eady growth rate bias (−0.1 day−1). Downscaling CanESM2 with CanRCM4 increases EETC frequency by one third, which reduces the frequency bias to −22%, and increases maximum EETC precipitation by 22%. Anthropogenic greenhouse gas forcing is projected to decrease EETC frequency (−15%, −18%) and Eady growth rate (−0.2 day−1, −0.2 day−1), and increase maximum EETC precipitation (46%, 52%) in CanESM2 and CanRCM4, respectively. The limited effect of dynamical downscaling on EETC frequency projections is consistent with the lack of impact on the maximum Eady growth rate. The coarse spatial resolution of GCMs presents an important limitation for simulating extreme ETCs, but Eady growth rate biases are likely just as relevant. Further bias reductions could be achieved by addressing processes that lead to an underestimation of lower tropospheric meridional temperature gradients

Attributing northern high-latitude precipitation change over the period 1966–2005 to human influence

Using an optimal fingerprinting method and improved observations, we compare observed and CMIP5 model simulated annual, cold season and warm season (semi-annual) precipitation over northern high-latitude (north of 50A degrees N) land over 1966-2005. We find that the multi-model simulated responses to the effect of anthropogenic forcing or the effect of anthropogenic and natural forcing combined are consistent with observed changes. We also find that the influence of anthropogenic forcing may be separately detected from that of natural forcings, though the effect of natural forcing cannot be robustly detected. This study confirms our early finding that anthropogenic influence in high-latitude precipitation is detectable. However, in contrast with the previous study, the evidence now indicates that the models do not underestimated observed changes. The difference in the latter aspect is most likely due to improvement in the spatial-temporal coverage of the data used in this study, as well as the details of data processing procedures.111911Ysciescopu

Reduced Tie2 in Microvascular Endothelial Cells Is Associated with Organ-Specific Adhesion Molecule Expression in Murine Health and Endotoxemia

Endothelial cells (ECs) in the microvasculature in organs are active participants in the pathophysiology of sepsis. Tyrosine protein kinase receptor Tie2 (Tek; Tunica interna Endothelial cell Kinase) is thought to play a role in their inflammatory response, yet data are inconclusive. We investigated acute endotoxemia-induced changes in the expression of Tie2 and inflammation-associated endothelial adhesion molecules E-selectin and VCAM-1 (vascular cell adhesion molecule-1) in kidneys and lungs in inducible, EC-specific Tie2 knockout mice. The extent of Tie2 knockout in healthy mice differed between microvascular beds, with low to absent expression in arterioles in kidneys and in capillaries in lungs. In kidneys, Tie2 mRNA dropped more than 70% upon challenge with lipopolysaccharide (LPS) in both genotypes, with no change in protein. In renal arterioles, tamoxifen-induced Tie2 knockout was associated with higher VCAM-1 protein expression in healthy conditions. This did not increase further upon challenge of mice with LPS, in contrast to the increased expression occurring in control mice. Also, in lungs, Tie2 mRNA levels dropped within 4 h after LPS challenge in both genotypes, while Tie2 protein levels did not change. In alveolar capillaries, where tamoxifen-induced Tie2 knockout did not affect the basal expression of either adhesion molecule, a 4-fold higher E-selectin protein expression was observed after exposure to LPS compared to controls. The here-revealed heterogeneous effects of absence of Tie2 in ECs in kidney and lung microvasculature in health and in response to acute inflammatory activation calls for further in vivo investigations into the role of Tie2 in EC behavior. </p

Childhood abuse and deprivation are associated with distinct sex-dependent differences in brain morphology

Childhood adversity (CA) has been associated with long-term structural brain alterations and an increased risk for psychiatric disorders. Evidence is emerging that subtypes of CA, varying in the dimensions of threat and deprivation, lead to distinct neural and behavioral outcomes. However, these specific associations have yet to be established without potential confounders such as psychopathology. Moreover, differences in neural development and psychopathology necessitate the exploration of sexual dimorphism. Young healthy adult subjects were selected based on history of CA from a large database to assess gray matter (GM) differences associated with specific subtypes of adversity. We compared voxel-based morphometry data of subjects reporting specific childhood exposure to abuse (n = 127) or deprivation (n = 126) and a similar sized group of controls (n = 129) without reported CA. Subjects were matched on age, gender, and educational level. Differences between CA subtypes were found in the fusiform gyrus and middle occipital gyms, where subjects with a history of deprivation showed reduced GM compared with subjects with a history of abuse. An interaction between sex and CA subtype was found. Women showed less GM in the visual posterior precuneal region after both subtypes of CA than controls. Men had less GM in the postcentral gyms after childhood deprivation compared with abuse. Our results suggest that even in a healthy population, CA subtypes are related to specific alterations in brain structure, which are modulated by sex. These findings may help understand neurodevelopmental consequences related to C

Depressive Symptoms and Amygdala Volume in Elderly with Cerebral Small Vessel Disease: The RUN DMC Study

Introduction. Late onset depressive symptoms (LODSs) frequently occur in elderly with cerebral small vessel disease (SVD). SVD cannot fully explain LODS; a contributing factor could be amygdala volume. We investigated the relation between amygdala volume and LODS, independent of SVD in 503 participants with symptomatic cerebral SVD. Methods. Patients underwent FLAIR and T1 scanning. Depressive symptoms were assessed with structured questionnaires; amygdala and WML were manually segmented. The relation between amygdala volume and LODS/EODS was investigated and adjusted for age, sex, intracranial volume, and SVD. Results. Patients with LODS had a significantly lower left amygdala volume than those without (P = 0.02), independent of SVD. Each decrease of total amygdala volume (by mL) was related to an increased risk of LODS (OR = 1.77; 95% CI 1.02–3.08; P = 0.04). Conclusion. Lower left amygdala volume is associated with LODS, independent of SVD. This may suggest differential mechanisms, in which individuals with a small amygdala might be vulnerable to develop LODS

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Prediction (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the "hiatus", volcanoes), including the study of the mechanisms that determine these behaviours. Groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society